The Four Types of Sales Professionals

Sales professionals create value in the mind of the customer. Period. They don’t persuade, they don’t trick, they don’t deceive. They create value, regardless of industry vertical or deal size. But sales professionals create value in different ways. In this post, I’ll outline the 4 fundamental kinds of sales value creation. Many sales jobs will not perfectly fit into one of these categories. However, all sales jobs can be predominantly characterized as one of the following.

Order takers

These people are technically sales professionals in job title, but they create only marginal value in the mind of the customer. They exist to answer the phone (or worse, fax), enter information into a system, and process payments. They don’t really sell in the traditional sense of the word. Order takers do not exist in startups. Order takers exist in commodity businesses in which both parties have long understood exactly what’s being sold, the value of the product service, and have an intuitive sense of the price. They also exist when startups grow up into real companies well after they’ve achieved Initial Scale at ~$10M ARR and are on a clear path to $100M ARR.

SalesForce is a great example. Although SalesForce offers a self-serve option, they employ hundreds (maybe thousands?) of people who deal with SMBs who are paying just a few hundred dollars per month. These sales people aren’t doing any selling. The SalesForce brand is selling itself. These sales people may answer some questions about billing and some features for customers, but they don’t carry quota, and they aren’t doing any material value creation in the mind of the customer.

Airlines are a great example of a commodity business that employs order takers. Airlines still employ thousands of people who answer the phone and place orders into ticketing systems. Big companies know that order takers are purely a cost center. The brand and the marketing has done all of the value-creation in the mind of the consumer, so the order taker is left purely as a cost center. As such, most airlines actually charge customers an additional fee to place orders by phone as a way to encourage consumers to buy online, where no human cost is involved. Airlines have literally decided to pass the cost of order takers onto consumers.

Similarly, SpareFoot, an Austin company, just shuttered its call center. Why? They removed the 800-number from every page of their website and instead drove traffic to online self-serve channels. When they flipped this switch, they obviated the need for 84 call center staff. Assuming a fully loaded cost of $50,000 / employee / year, SpareFoot just added $4.2M / year back to the bottom line. That’s a huge profit lift considering that SpareFoot is orders of magnitude smaller than SalesForce or airlines. Just imagine how much money those companies spend on order takers.

Volume Players

Volume players can be easily confused with stereotypical sleazy sales people. Some volume players are indeed sleazy, but many aren’t. Volume players are used car sales professionals, people who try to sell magazine subscriptions over the phone, and Sales Development Reps (SDRs) who sell low annual contract value (ACV) products. Examples include Yodle, MainStreetHub, andOutbound Engine. All of these companies sell to SMBs and their price points don’t exceed $300 or $400 / month. These companies probably have SDRs and Account Executives (AEs) in the sales cycle, but their business is really just a numbers game. They employ some order takers, but most of their sales staff are dialing for dollars.

The beautiful thing about volume players is that the sales cycles are short and relatively easy. They typically have a low conversion rate, which is exactly why volume players are volume players: they have to make up for low conversion rates in volume. The low conversion rate isn’t the fault of the sales professional; rather, it’s just typical of low ACV customers. Volume players create value in the mind of the buyer, but the purchase decision is in many cases made on a whim (easily characterized by 1-call closes), or made through the lens of “I’ll try it for a month, it will only cost a few hundred bucks, and kill it if it isn’t working.” There’s nothing wrong with that thinking through the lens of the customer. If the product works as advertised, then everyone has won: the customer has extracted value from the product/service, the company has provided value, the company has generated profit, and sales professional has earned her commission.

Volume players live and die by the rules of the system. The VP Sales and sales ops leaders design the system, and the volume player SDRs and AEs live in the system. They thrive in it. The rules are clearly defined, comp plans are crystal clear, every objection and concern has already been considered, everything is mapped out in SalesForce/SalesLoft, and there is almost no ambiguity or material decision that needs to be made at any point in a given sales process once a sales professional is trained and up-to-speed. It’s easy to identify the best volume players: they work at companies that have optimized the system to a teel, and they more than double their base salary with variable comp. They are looking for structure and support from their employer so they can focus on creating value in the mind of the customer without any distractions.

SDRs who sell high ACV products are often volume players as well. However, they only operate at the top of the sales funnel, and can afford to think in terms of volume. AEs who sell high ACV ($50K+) products are…

Magicians

Magicians create material value in the mind of the customer where there was once no value. That’s why they are magicians. They create something out of nothing. This is real enterprise selling. It’s also by far the most difficult form of sales. The best magicians take home $1M+ / year after taxes.

Magicians sell novel, high ACV products. That means magicians only really exist in enterprise technology sales. Very few other products fit that mold.

The 1st step to becoming a magician is to develop a deep understanding of the customer. Magicians learn everything they can about their current customers’ existing processes, workflows, and problems. They become industry experts. No detail is too trivial.

The very best magicians don’t want to figure out the basics on their own. They expect to spend the first 30 days going through rigorous sales training that has already been devised and laid out for them by the VP Sales and sales ops leadership. Early stage CEOs are by definition magicians. They have to literally figure out all of the consumer’s paint points, and what messaging resonates with them. Overtime, the CEO will work with sales leadership to extract all of the information from the CEO’s brain and turn it into a magician-factory, AKA a sales training program.

There will be a phase from $500K — $5M ARR where the sales training system isn’t fleshed out to support the best magicians. This is the hardest phase in which to hire magicians. The best magicians will know exactly what kind of supporting infrastructure they need. They’ll figure this out with just a few questions:

1. Have you built out a full customer lifecycle map with all of the relevant stakeholders, the the key concerns and objections they have, and relevant materials to overcome those objections?
2. Do you have half a dozen case studies on the website of customers who are paying $[median ACV * 1.5]?
3. What are the top 2 reasons VPs buy the product?

Real magicians know that if the company can’t answer these questions (and many more) in two sentences or less, the infrastructure isn’t ready to support them. They know what they need.

The phase between $500K and $5M ARR is tough. The CEO sold the first $500K haphazardly. That’s standard. But as the company passes $1M ARR, the CEO will need help. The CEO can’t maintain 15% m/m growth as the numbers become ever-larger. But real magicians won’t join because they know they won’t make as much money as they will if they stay at their current, larger, more mature company.

Finding people who will become magicians but aren’t yet is incredibly difficult. They have to be smart enough to think on their feet and adaptable, they have to understand the customer, they have to learn real enterprise selling, they have to know they will lose deals simply because the company hasn’t encountered all of the variables yet, but not yet far enough along in their careers to have comp expectations > $250K. That’s a very fine needle to thread.

Over the last 30 years, the sales process has become increasingly value-creation focused. There was a time (so I’m told) where $10M deals were sold based on relationships. This is by and large not the case in enterprise technology anymore due to any number of factors: the cloud, free information on the Internet, social media, technology maturity, etc. Today, magicians conduct enterprise sales.

Note, magicians come by many names: enterprise sales professionals, consultative sales, etc.

Relationship Based Selling

This is “old boys” sales. This involves wining and dining customers, playing golf with them, and doing anything possible to spend time with the customer. Per the Benjamin Franklin effect, if someone spends that much time with another person, how can they not like one another?

Relationship based selling is by and large gone today in enterprise technology. But it still exists in many other industries including real estate, pharmaceutical, and med device. These sales processes only work for high ACV items because the cost of maintaining the relationship is high.

The worst examples of this exist in the implantable med device industry. I have met medical device reps who are proud of the fact that they pick up surgeons’ dry cleaning. This process is being curbed by the growth of value analysis committees in hospitals, but it is still prevalent in in healthcare, where sophisticated med device and pharma companies charge copious amounts of money to insurance companies to justify ridiculously inflated sales costs.

Relationship-based sales professionals are easy to spot during the interview process. They’ll ask early on what the T&E budget is because they are used to abusing generous big company T&E policies that are designed to support relationship based sales. They probably have gone over the T&E allocation a few times, have been scolded for it, and as such are particularly worried about how many $100 dinners they can purchase for themselves on the company’s dime. Moreover, they aren’t typically that interested in really understanding the customer’s problems. They are just more interested in being nice to the customer and being her best friend because that’s easy and worked for them in the past. Relationship-focused sales professionals will probably come to the interview with a superficial understanding of the problem the company is solving and how company’s solution goes about solving it. Why? Because they expect the system to teach them what they need to know, and then they expect to go out and just spend time with customers and get customers to like them. They will lack the native motivation to dive deep into the industry and become experts.

The Deception of Positive and Negative Growth Percentages

Growth and decline percentages are deceiving in the startup universe. Many don’t recognize all of the implications of exponential growth and the associated hiring challenges. This problem manifests most commonly when a startup begins to achieve product/market fit and Initial Traction (~$1M ARR). 

When a startup is growing 10-15% m/m on the path from $500K - $1M ARR, the startup is adding $50-$100K in ARR each month, or $4-8K MRR. 10% m/m growth isn’t bad, but it’s not great. Great startups are growing > 15% m/m as they pass $1M ARR, and the Select Few are growing >25% m/m.

But what many fail to recognize is how the math scales. At $1M ARR, growing 15% m/m requires adding $150K in ARR, or $12.5K in MRR each month. Thus, from the time a startup achieves $1M ARR, they should hit $1.5M ARR in 3 months if they want to maintain 15% m/m growth.

At $1.5M ARR, 15% m/m growth means the startup needs to add $225K in MRR each month. So the startup should grow from $1.5M to $2M in just over 2 months, or 33% faster than the prior $500K in ARR.

This math isn’t particularly difficult to understand. But many underestimate just how hard it is to accelerate growth as the numbers get bigger. There are tons of startups that get to a point of adding $100K in ARR each month. 10x-ing that - adding $1M in ARR each month - requires real thought and and planning. Jason Cohen of WPEngine describes this problem very well. At a rate of adding $1M ARR each month, it will take 100 months, or more than 8 years, to achieve $100M ARR. Growth has to accelerate.

How does all of this tie to hiring? As startups add multiple customer acquisition channels, hire more than 2 sales people, and generally scale, startups need to invest in infrastructure. All kinds of it. This means marketing automation, sales automation, and customer success automation - collectively customer lifecycle systems and processes - to accelerate growth. There should be minimal innovation around these disciplines: innovate myopically. But startups need to hire the right people so that they don’t have to innovate in these disciplines. Tech/product focused founders rarely have expertise setting up customer lifecycle systems and processes. They should bring in the people who have implemented those processes before, and empower them to do it.

Those people are going to be more expensive than many founders naturally think. I remember the first time I looked at what an amazing VP Customer Success costs after raising a Series A. I couldn’t believe it: $150-$200K and .5%-1.5%. Great VP Sales can go much higher. But the great ones are worth their salary 10x over. Because they will make the startups’ customers happy in a way the founders otherwise never could, and those customers will fuel the best kind of growth: word-of-mouth (WOM). Not only does WOM scale incredibly well, it scales well inexpensively, driving down CAC and ensuring that startups don’t compromise the fundamental law of startup growth (fantastic post). That amazing VP Customer Success will drive down CAC and drive up LTV, ensuring the startup stays venture-fundable as it scales to $100M ARR. The amazing VPs are worth any amount of cash and equity to acquire.

The situation is particularly amplified for companies that are doing $1-2M ARR and are 4+ years old. If the product/market fit is tight and the market opportunity is real, then that means the startup needs serious customer acquisition help across all fronts. If there were any top notch marketing or sales people around, they probably left because they didn’t have the help around them they needed to drive revenue growth. And so now the company is left with B players without strong customer acquisition and customer success leadership. Those companies are the ones that most need to find a spark  to rethink the entire customer acquisition process and ignite growth. Those people will be expensive in cash and equity terms, but if they are any good, they will be worth their cost 100x over. As Jason Lemkin of SaaStr loves to say, salary and equity vest (and equity has a cliff), so the cost of being wrong is relatively low given the slow growth rate anyways.

Hiring becomes even more important when thinking about growth given the time cycles involved. Hiring great executives takes months, and onboarding takes 30-60 days, so founders need to have incredible foresight to time VP-level hires right to ensure they maintain an exponential growth curve. That means in many cases it will take 6 months to hire and onboard great VPs. So that means that startups should start looking for their first great VP hires between $500K - $1M ARR. If the startup is growing is 15% m/m and it takes 6 months to find and onboard the VP, then the startup will be at $1M-$2M ARR - or double the revenue of when the search started - before the VP is delivering material value. This is not intuitive to founders who, up until this point, have been able to tweak almost anything overnight other than the product fuel growth. It’s not naturally intuitive to think that a single thing - hiring an executive - will take 6 months. Exponential growth can be deceiving.

The flip side of thinking about growth - which is theoretically unlimited - is thinking about a fixed pie. And this is where percentages are really deceiving. When discussing negative percentages - revenue declines, accelerating burn, etc - it feels like the pie is being eaten… because it is. These are fixed pie scenarios. All of a sudden, 15% of the pie is gone. It feels like crap because psychology dictates that humans strongly prefer loss aversion to gains.

The problem that many entrepreneurs make is applying the same fixed-pie mindset and applying it to growth percentages and thinking about equity value. Positive and negative percentages need to be thought through opposing lenses: negative percentages should be thought of as a fixed pie that’s being eaten, while positive percentages need to be thought through the lens of infinite growth. Companies can become infinitely large - see Apple and Google - so the real dilemma isn’t how to minimize losses, but how to maximize growth. All decisions should be made through the lens of maximizing growth, even if material costs are incurred. Startups can always grow more than they can lose (unless gross margins are negative, in which case the business shouldn’t exist). Invest in that growth, even if it feels expensive through a fixed-pie lens. 6 months later, it will feel like a bargain when looking backwards through an infinite growth lens.

Understanding the Millennial Mindset

As I read this Fortune piece that outlines how and why millennials are investing with robo financial advisors (eg Wealthfront, Betterment) in place of traditional financial advisors (eg Schwab, Fidelity), I couldn’t help but think about the broader divide between the mindset of millennials and prior generations.

The Internet has completely changed everything.

I was born in 1990. I began using Google when I was 9. At the age of 9, I learned that I can access any piece of information for free, instantly. I remember trying to access Encyclopedia Brittanica (Microsoft’s online encyclopedia in the days before Wikipedia), and I was confused why they charged so much money — hundreds of dollars — for what I thought was a free commodity: information. I asked my Dad, someone who built his career on the Microsoft stack (Microsoft made their money charging for software; Google made their money giving software away for free), why the information was so expensive. He told me that it was expensive to pay people to curate the information, and that the only way Microsoft could justify Encyclopedia Britannica’s existence was to charge for access to that information. I didn’t like his answer because I loved the ease and simplicity of Google search. But he was right: humans are expensive.

Then Wikipedia emerged in 2001 and systematically dismantled Encyclopedia Britannica and all of the other online encyclopedias. Since then, Internet economics have come to dictate that all information should be free. I am no longer the in exception in thinking that information should be free and freely available to everyone. The vast majority of information is already freely available to the public, and the public has come to expect that information should be free. For every company selling proprietary information, there are a dozen tech startups trying to dismantle legacy information arbitrage businesses.

This is the difference between the millennial mindset. When my father was growing up, he had to turn to a financial advisor to manage his personal capital. He had to go to a doctor’s office and wait in line to seek medical help. He had to call a travel agent to not only book plane tickets, but to even find out when flights were departing. And he not only had to interact with others to get this information, he had to pay for information (the cost of information dispersion was built into cost of the service). The people whom he spoke to had to draw salaries. Millions of businesses were built, some large, some small, that just sold access to information. These were information arbitrage businesses. Internet economics destroy information arbitrage opportunities.

I grew up assuming that I could access everything for free. When Encylopedia Britannica tried to charge me to learn about nature, I was confused. This is the root of the millennial mindset: that I can learn anything about anything on my own and be reasonably self-sufficient. Most millennials know that they aren’t physicians and that they aren’t sophisticated money managers, but they also know intuitively and intrinsically that these services shouldn’t be as expensive as they were because at their core, these are just information arbitrage services. Paying for information doesn’t make sense to millennials.

The Internet is the most democratizing technology ever invented, and my generation has absorbed this in a way that most others in prior generations have not. This is the millennial mindset.

PS, the Internet is the most capitalistic invention since the invention of capitalism itself. One of the core tenets of capitalism is that consumers have complete information of what they are buying — the quality of the product, the price, prices for competitive services and items, etc. The Internet empowers consumers by reducing the cost of information to $0. Capitalism fuels the millennial mindset, and the millennial mindset fuels capitalism. It’s a beautiful, virtuous cycle.

PPS, there are still many legacy businesses predicated on information arbitrage. They are most heavily concentrated around the government: tax advisors, FDA consultants, etc. I suspect we’ll see these services democratize over the next 30 years, but it will be a slow, long haul.

Should Your Startup Go Full Stack?

I’ve written about the problems associated with selling into value chains where there are disparate P&Ls. In this post, I’ll dive into the solution to this problem: going full stack. I’ll also cover when going full stack makes sense.

Chris Dixon of a16z has noted the rise of a number of high-profile, full stack startups across many industry verticals. What is a full stack startup? Full stack startups are those that, rather than selling a novel piece of technology to incumbents, use the technology they’ve built to serve the incumbent’s customers directly, bypassing the incumbent in the process. There are many of examples of modern full stack startups and their respective antitheses. A few examples:

Uber vs Hailo - Everyone knows that Uber bypassed taxis and instead when straight to the end consumer. On the other hand, Hailo responded to Uber by selling an Uber-like platform to local taxi companies. Hailo has struggled while Uber has run away with the market.

Buzzfeed vs ThoughtLeadr - BuzzFeed is changing the media business because their entire strategy is based on sourcing and producing content that’s designed to be easily consumed through the best discovery channels: social media. Everything they do stems from a deep understanding of how users share content. As a result of that, they have devised an incredible formula that seamlessly intertwines native advertising with socially shared digital content. ThoughtLeadr and many companies like it are trying to empower media organizations to rethink content strategy and distribution around native advertising and social sharing. BuzzFeed does the tech and content production in house. To be clear, I am close with the team at ThoughtLeadr, and I actually love what they’re doing. BuzzFeed can’t be the only media property on the planet. The world needs companies that can help old-school media properties thrive in the digital age. ThoughtLeadr is doing just that.

Oscar vs traditional healthcare insurers - Oscar recognized that health insurance should be completely rethought around smartphones. Smartphones enable new models where insurers consume vastly more consumer data (think movement, etc), and present a potent communication medium. Rather than trying to help traditional health insurers transform their entire businesses - customer acquisition, service, preventative care, etc - Oscar decided to build a brand new health insurance company that didn’t have any legacy baggage.

HealthSpot vs Teladoc - Teladoc owns and operates its own technology to enable virtual physician consults, whereas HealthSpot built/assembled technology and sold it to provider organizations. Healthspot recently ceased operations, while Teladoc recently IPO’d and is growing hand-over-fist as healthcare continues to consumerize.

One Medical Group (OMG) and Kaiser Permanente (KP) vs traditional healthcare providers - KP and OMG are two prominent examples of “full stack” healthcare providers. KP is enormous and has been around for a while and operates as an health plan and fully-featured provider organization. OMG is the leading pioneer of the Direct Primary Care model, which borrows many health-plan like features and functions. These organizations both invest heavily in their own technology development, and use that to offer differentiated healthcare services to their customers. KP and OMG stand in stark contrast to more traditional healthcare providers, who simply make money for doing stuff to patients.

I don’t mean for these examples to paint the picture that being full stack is always the right answer, and that being partial stack is the wrong answer. There are many successful companies that are explicitly not full stack: Workday, SalesForce, Slack, Zenefits, etc. These startups have been successful partial stack companies because they do not break the daily workflow of their users.

For example, let's look at SalesForce. Although sales professionals like to complain that SalesForce is clunky, slow and a not helpful in their daily workflow, SalesForce is just a tool that’s designed to reinforce a process that the sales people should have been adhering to in a paper world: contact and pipeline management. Zenefits users are still buying health insurance, and still filling out forms. The process itself really hasn’t changed; all Zenefits has done is unemploy health insurance brokers. Slack users are still designing, coding, etc; with Slack, they can collaborate with their colleagues more effectively. The same can be said of the other examples above.

On the other hand, tech companies should consider going full stack if they break the operational processes of the primary users of their solution. Uber could never sell into the taxi industry because Uber commoditized taxis, and taxi company owners didn’t want to subject themselves to that. Oscar could never sell its novel technology to traditional health insurers because it would have required rethinking every function in the insurance company. HealthSpot couldn’t usher traditional healthcare providers into a retail care delivery model.

Why can’t incumbents adopt technology solutions that completely break the daily workflow of their primary revenue-generating employees? In short, it’s too operationally disruptive. The organizations simply cannot absorb the change. When an employee’s daily workflow is completely rethought, the vast majority of her existing operational knowledge is not only worthless, but actually destructive in the new paradigm. Processes that made sense in the old paradigm no longer make sense in the new paradigm. Convincing thousands of employees and managers across disparate geographies and changing incentive structures to unlearn bad habits (to be fair, they were good habits in the old paradigm) is nearly impossible. In the case of Oscar, this is even more problematic as the changes would have spanned employees across every function in the company. Old and new paradigms simply cannot coexist in the same organization. Note: this is the fundamental problem that Clayton Christensen details in The Innovator's Dilemma.

As we see more verticals SaaS-ify, I suspect most startups will rightfully decide not to go full stack. For example, TalkDesk, ServiceMax, and Veeva rightfully didn't go full stack.  Although the new wave of vertical-SaaS vendors strive to be the all important system of record, they are generally seeking to re-inforce processes that should have already existed. In most cases, SaaS solutions are not radically changing the cost structure associated with delivering the services in question and are not re-inventing the business.

In summary, startups should go full stack if they are going to genuinely break the workflow of their target user. Otherwise, they should go partial stack.

PS, Given my background in electronic medical records (EMR), I'll add some commentary to that industry. EMRs break the daily workflow of the primary revenue generating employees of healthcare provider organizations. So why haven't EMR vendors gone full stack? Not a single traditional EMR vendor has even tried to offer healthcare services. There are a few reasons: during the golden era of EMRs, telemedicine wasn't reimbursable, so it wasn't practical to consolidate providers centrally given the intrinsically local nature of healthcare delivery. On the other hand, every novel tech-enabled healthcare service builds and manages its own technology in house: One Medical Group, Doctor on Demand, Teladoc, etc. The providers that are pioneering new delivery models recognize the importance of technology in their new models and are rightfully insourcing it to go full stack. This tech investment also serves as their barrier to entry and differentiator.

Online Dating Empowers Women

I'll preface this blog post by saying that this blog post is meant to highlight trends in America in the 2005-2015 era. This post isn't meant to be a 100% accurate, definitive truth about dating. There are millions of women who will say this doesn't apply to them, and that's right. I acknowledge this. Rather, this post is meant to articulate the changes online dating has brought to a significant percentage of women in America. Here we go:

Before the Internet became commonplace in America, American women generally met men in one of two ways: out at a bar, or through a referral. In the last few years, online dating has exploded on mobile devices and has become a major channel through which men and women connect. For the purposes of this blog post, I’ll outline some of the key differences between online dating, meeting women out at bars, and referrals that I’ve observed as a single male in my mid twenties living in Austin, TX.

Defenses - women generally have their defenses up when they’re out at bars at night. They know men are out to hit on them, that most men are trashy, and as a result, women explicitly choose to play “hard to get.” This is entirely rational behavior given the general male populace. Contrast this with online dating, in which there’s no need to have one’s defenses up. Women can choose who they want to speak to online, and block those whom they don’t. Although women can always end a conversation when out at a bar, it’s a lot harder to leave a physical, in-person conversation due to social pressure and logistical space constraints than to simply hit the “block” button on a mobile app.

Solo vs groups - as a man, it’s dramatically more difficult to approach a group of women rather than just one. This makes it very difficult to get one-on-one time with the woman I’m trying to speak with, simply because she’s with a group of friends. Women rarely go out alone. But online, all conversations happen in one-on-one settings. This enables men to speak to women who they otherwise wouldn’t have been able to, and conversely allows women to speak to men who they otherwise wouldn’t have spoken to.

Inversely, women act differently individually than they do in groups. When they’re out with friends, there is a certain level of group-think at play. The woman generally follows the wishes of the collective group, even if she would prefer not to. Similarly, women will speak differently with men when they know their friends are around than when friends aren’t around. A woman may choose to flirt less with a man because she knows her friends are around than if her friends weren’t.

Power to choose - women can choose who they want to have conversations with online. Although this is technically true out at bars, in practice women have little control over who they speak when they’re out. Through the course of a night, any number of men may approach a woman. Women are free to reject the men, but aren’t typically going up to speak to men. There are exceptions, but in general, women are waiting to be hit on. But online, services like Tinder and Bumble explicitly force women to opt into the conversation before the conversation even starts. This means women don’t waste their time with men who they don’t want to, and vice versa. Rejecting a group of men in person is substantially more difficult than it is to reject a single man online.

Similarly, online dating makes it much easier for women to proactively reach out to men that they’d like to speak to. Although women can always talk to a man out a bar, it’s much more difficult to approach a strange man at a bar than it is online. Moreover, since women aren’t expected to speak to strange men out at bars, women have less practice talking to strangers at bars than men do, compounding the problem further.

Online dating radically changes the dating process. Rather than going out and hoping to be hit on, women can very proactively manage the "top of the funnel" in their dating lives by leveraging technology. Women can manage this process discreetly, with no external pressure, motivations, or constraints. Specifically, online dating empowers women to: talk to more men, talk to more men that they would like to speak to, quickly filter out the men that they don’t want to speak to, speak to men without the social pressure that friends exert on them, and to reach out to men that they otherwise wouldn’t have. Although apps like Tinder have created a perception that online dating exists only to support "hook ups," this is patently false. There are many desirable characteristics of online dating, and that's exactly why men and women alike have adopted dating apps like Tinder so quickly.